How to use _create_metrics_plot_helper method in autotest

Best Python code snippet using autotest_python Github


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...431 plot['errors'] = new_errors432 plot['y'], plot['errors'] = _normalize(plot['y'], plot['errors'],433 new_base_values,434 new_base_errors)435def _create_metrics_plot_helper(plot_info, extra_text=None):436 """437 Create a metrics plot of the given plot data.438 plot_info: a MetricsPlot object.439 extra_text: text to show at the uppper-left of the graph440 TODO(showard): move some/all of this logic into methods on MetricsPlot441 """442 query = plot_info.query_dict['__main__']443 cursor = readonly_connection.cursor()444 cursor.execute(query)445 if not cursor.rowcount:446 raise NoDataError('query did not return any data')447 rows = cursor.fetchall()448 # "transpose" rows, so columns[0] is all the values from the first column,449 # etc.450 columns = zip(*rows)451 plots = []452 labels = [str(label) for label in columns[0]]453 needs_resort = (cursor.description[0][0] == 'kernel')454 # Collect all the data for the plot455 col = 1456 while col < len(cursor.description):457 y = columns[col]458 label = cursor.description[col][0]459 col += 1460 if (col < len(cursor.description) and461 'errors-' + label == cursor.description[col][0]):462 errors = columns[col]463 col += 1464 else:465 errors = None466 if needs_resort:467 y = _resort(labels, y)468 if errors:469 errors = _resort(labels, errors)470 x = [index for index, value in enumerate(y) if value is not None]471 if not x:472 raise NoDataError('No data for series ' + label)473 y = [y[i] for i in x]474 if errors:475 errors = [errors[i] for i in x]476 plots.append({477 'label': label,478 'x': x,479 'y': y,480 'errors': errors481 })482 if needs_resort:483 labels = _resort(labels, labels)484 # Normalize the data if necessary485 normalize_to = plot_info.normalize_to486 if normalize_to == 'first' or normalize_to.startswith('x__'):487 if normalize_to != 'first':488 baseline = normalize_to[3:]489 try:490 baseline_index = labels.index(baseline)491 except ValueError:492 raise ValidationError({493 'Normalize' : 'Invalid baseline %s' % baseline494 })495 for plot in plots:496 if normalize_to == 'first':497 plot_index = 0498 else:499 try:500 plot_index = plot['x'].index(baseline_index)501 # if the value is not found, then we cannot normalize502 except ValueError:503 raise ValidationError({504 'Normalize' : ('%s does not have a value for %s'505 % (plot['label'], normalize_to[3:]))506 })507 base_values = [plot['y'][plot_index]] * len(plot['y'])508 if plot['errors']:509 base_errors = [plot['errors'][plot_index]] * len(plot['errors'])510 plot['y'], plot['errors'] = _normalize(plot['y'], plot['errors'],511 base_values,512 None or base_errors)513 elif normalize_to.startswith('series__'):514 base_series = normalize_to[8:]515 _normalize_to_series(plots, base_series)516 # Call the appropriate function to draw the line or bar plot517 if plot_info.is_line:518 figure, area_data = _create_line(plots, labels, plot_info)519 else:520 figure, area_data = _create_bar(plots, labels, plot_info)521 # TODO(showard): extract these magic numbers to named constants522 if extra_text:523 text_y = .95 - .0075 * len(plots)524 figure.text(.1, text_y, extra_text, size='xx-small')525 return (figure, area_data)526def create_metrics_plot(query_dict, plot_type, inverted_series, normalize_to,527 drilldown_callback, extra_text=None):528 plot_info = MetricsPlot(query_dict, plot_type, inverted_series,529 normalize_to, drilldown_callback)530 figure, area_data = _create_metrics_plot_helper(plot_info, extra_text)531 return _create_image_html(figure, area_data, plot_info)532def _get_hostnames_in_bucket(hist_data, bucket):533 """\534 Get all the hostnames that constitute a particular bucket in the histogram.535 hist_data: list containing tuples of (hostname, pass_rate)536 bucket: tuple containing the (low, high) values of the target bucket537 """538 return [hostname for hostname, pass_rate in hist_data539 if bucket[0] <= pass_rate < bucket[1]]540def _create_qual_histogram_helper(plot_info, extra_text=None):541 """\542 Create a machine qualification histogram of the given data.543 plot_info: a QualificationHistogram544 extra_text: text to show at the upper-left of the graph545 TODO(showard): move much or all of this into methods on546 QualificationHistogram547 """548 cursor = readonly_connection.cursor()549 cursor.execute(plot_info.query)550 if not cursor.rowcount:551 raise NoDataError('query did not return any data')552 # Lists to store the plot data.553 # hist_data store tuples of (hostname, pass_rate) for machines that have554 # pass rates between 0 and 100%, exclusive.555 # no_tests is a list of machines that have run none of the selected tests556 # no_pass is a list of machines with 0% pass rate557 # perfect is a list of machines with a 100% pass rate558 hist_data = []559 no_tests = []560 no_pass = []561 perfect = []562 # Construct the lists of data to plot563 for hostname, total, good in cursor.fetchall():564 if total == 0:565 no_tests.append(hostname)566 continue567 if good == 0:568 no_pass.append(hostname)569 elif good == total:570 perfect.append(hostname)571 else:572 percentage = 100.0 * good / total573 hist_data.append((hostname, percentage))574 interval = plot_info.interval575 bins = range(0, 100, interval)576 if bins[-1] != 100:577 bins.append(bins[-1] + interval)578 figure, height = _create_figure(_SINGLE_PLOT_HEIGHT)579 subplot = figure.add_subplot(1, 1, 1)580 # Plot the data and get all the bars plotted581 _,_, bars = subplot.hist([data[1] for data in hist_data],582 bins=bins, align='left')583 bars +=[-interval], len(no_pass),584 width=interval, align='center')585 bars +=[bins[-1]], len(perfect),586 width=interval, align='center')587 bars +=[-3 * interval], len(no_tests),588 width=interval, align='center')589 buckets = [(bin, min(bin + interval, 100)) for bin in bins[:-1]]590 # set the x-axis range to cover all the normal bins plus the three "special"591 # ones - N/A (3 intervals left), 0% (1 interval left) ,and 100% (far right)592 subplot.set_xlim(-4 * interval, bins[-1] + interval)593 subplot.set_xticks([-3 * interval, -interval] + bins + [100 + interval])594 subplot.set_xticklabels(['N/A', '0%'] +595 ['%d%% - <%d%%' % bucket for bucket in buckets] +596 ['100%'], rotation=90, size='small')597 # Find the coordinates on the image for each bar598 x = []599 y = []600 for bar in bars:601 x.append(bar.get_x())602 y.append(bar.get_height())603 f = subplot.plot(x, y, linestyle='None')[0]604 upper_left_coords = f.get_transform().transform(zip(x, y))605 bottom_right_coords = f.get_transform().transform(606 [(x_val + interval, 0) for x_val in x])607 # Set the title attributes608 titles = ['%d%% - <%d%%: %d machines' % (bucket[0], bucket[1], y_val)609 for bucket, y_val in zip(buckets, y)]610 titles.append('0%%: %d machines' % len(no_pass))611 titles.append('100%%: %d machines' % len(perfect))612 titles.append('N/A: %d machines' % len(no_tests))613 # Get the hostnames for each bucket in the histogram614 names_list = [_get_hostnames_in_bucket(hist_data, bucket)615 for bucket in buckets]616 names_list += [no_pass, perfect]617 if plot_info.filter_string:618 plot_info.filter_string += ' AND '619 # Construct the list of drilldown parameters to be passed when the user620 # clicks on the bar.621 params = []622 for names in names_list:623 if names:624 hostnames = ','.join(_quote(hostname) for hostname in names)625 hostname_filter = 'hostname IN (%s)' % hostnames626 full_filter = plot_info.filter_string + hostname_filter627 params.append({'type': 'normal',628 'filterString': full_filter})629 else:630 params.append({'type': 'empty'})631 params.append({'type': 'not_applicable',632 'hosts': '<br />'.join(no_tests)})633 area_data = [dict(left=ulx, top=height - uly,634 right=brx, bottom=height - bry,635 title=title, callback=plot_info.drilldown_callback,636 callback_arguments=param_dict)637 for (ulx, uly), (brx, bry), title, param_dict638 in zip(upper_left_coords, bottom_right_coords, titles, params)]639 # TODO(showard): extract these magic numbers to named constants640 if extra_text:641 figure.text(.1, .95, extra_text, size='xx-small')642 return (figure, area_data)643def create_qual_histogram(query, filter_string, interval, drilldown_callback,644 extra_text=None):645 plot_info = QualificationHistogram(query, filter_string, interval,646 drilldown_callback)647 figure, area_data = _create_qual_histogram_helper(plot_info, extra_text)648 return _create_image_html(figure, area_data, plot_info)649def create_embedded_plot(model, update_time):650 """\651 Given an EmbeddedGraphingQuery object, generate the PNG image for it.652 model: EmbeddedGraphingQuery object653 update_time: 'Last updated' time654 """655 params = pickle.loads(model.params)656 extra_text = 'Last updated: %s' % update_time657 if model.graph_type == 'metrics':658 plot_info = MetricsPlot(query_dict=params['queries'],659 plot_type=params['plot'],660 inverted_series=params['invert'],661 normalize_to=None,662 drilldown_callback='')663 figure, areas_unused = _create_metrics_plot_helper(plot_info,664 extra_text)665 elif model.graph_type == 'qual':666 plot_info = QualificationHistogram(667 query=params['query'], filter_string=params['filter_string'],668 interval=params['interval'], drilldown_callback='')669 figure, areas_unused = _create_qual_histogram_helper(plot_info,670 extra_text)671 else:672 raise ValueError('Invalid graph_type %s' % model.graph_type)673 image, bounding_box_unused = _create_png(figure)674 return image675_cache_timeout = global_config.global_config.get_config_value(676 'AUTOTEST_WEB', 'graph_cache_creation_timeout_minutes')677def handle_plot_request(id, max_age):...

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